6508results about "Genomics" patented technology

Embodiments of this invention provide methods, systems, and apparatus for determining whether a fetal chromosomal aneuploidy exists from a biological sample obtained from a pregnant female. Nucleic acid molecules of the biological sample are sequenced, such that a fraction of the genome is sequenced. Respective amounts of a clinically-relevant chromosome and of background chromosomes are determined from results of the sequencing. A parameter derived from these amounts (e.g. a ratio) is compared to one or more cutoff values, thereby determining a classification of whether a fetal chromosomal aneuploidy exists.

The invention provides methods for determining aneuploidy and / or fetal fraction in maternal samples comprising fetal and maternal cfDNA by massively parallel sequencing. The method comprises a novel protocol for preparing sequencing libraries that unexpectedly improves the quality of library DNA while expediting the process of analysis of samples for prenatal diagnoses.

“In silico” nucleic acid recombination methods, related integrated systems utilizing genetic operators and libraries made by in silico shuffling methods are provided.

The information management system disclosed enables caregivers to make better decisions, faster, using aggregated genetic and phenotypic data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects who may be at distributed facilities. A standardized data model stores a range of patient data in standardized data classes that encompass patient profile information, patient symptomatic information, patient treatment information, and patient diagnostic information including genetic information. Data from other systems is converted into the format of the standardized data classes using a data parser, or cartridge, specifically tailored to the source system. Relationships exist between standardized data classes that are based on expert rules and statistical models. The relationships are used both to validate new data, and to predict phenotypic outcomes based on available data. The prediction may relate to a clinical outcome in response to a proposed intervention by a caregiver. The statistical models may be inhaled into the system from electronic publications that define statistical models and methods for training those models, according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic and clinical data, in particular for underdetermined data sets that are typical of genetic information. The disclosure also describes how security of the data is maintained by means of a robust security architecture, and robust user authentication such as biometric authentication, combined with application-level and data-level access privileges.

The present invention relates to methods for achieving an optimal function of a biochemical reaction network. The methods can be performed in silico using a reconstruction of a biochemical reaction network of a cell and iterative optimization procedures. The methods can further include laboratory culturing steps to confirm and possibly expand the determinations made using the in silico methods, and to produce a cultured cell, or population of cells, with optimal functions. The current invention includes computer systems and computer products including computer-readable program code for performing the in silico steps of the invention.

The invention encompasses novel methods for developing a computer model of type 1 diabetes in a mammal. In particular, the models can include representations of biological processes associated with a pancreatic lymph node and one or more pancreatic islets. Alternatively, the models can include representations of biological processes associated with at least two conditions selected from the group consisting of autoreactive T cell production, autoreactive T cell priming, insulitis and hyperglycemia. The invention also provides methods for developing a computer model of a non-insulin replacement treatment of type 1 diabetes. The invention also encompasses computer models of type 1 diabetes, methods of simulating type 1 diabetes and computer systems for simulating type 1 diabetes and the uses thereof.

Disclosed is a method to achieve digital quantification of DNA (i.e., counting differences between identical sequences) using direct shotgun sequencing followed by mapping to the chromosome of origin and enumeration of fragments per chromosome. The preferred method uses massively parallel sequencing, which can produce tens of millions of short sequence tags in a single run and enabling a sampling that can be statistically evaluated. By counting the number of sequence tags mapped to a predefined window in each chromosome, the over- or under-representation of any chromosome in maternal plasma DNA contributed by an aneuploid fetus can be detected. This method does not require the differentiation of fetal versus maternal DNA. The median count of autosomal values is used as a normalization constant to account for differences in total number of sequence tags is used for comparison between samples and between chromosomes.

The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure. According to various embodiments, methods, systems and interfaces for associating experimental data, features and groups of data related by structure and / or function with chemical, medical and / or biological terms in an ontology or taxonomy are provided. According to various embodiments, methods, systems and interfaces for filtering data by data source information are provided, allowing dynamic navigation through large amounts of data to find the most relevant results for a particular query.

Embodiments of this invention provide methods, systems, and apparatus for determining whether a fetal chromosomal aneuploidy exists from a biological sample obtained from a pregnant female. Nucleic acid molecules of the biological sample are sequenced, such that a fraction of the genome is sequenced. Respective amounts of a clinically-relevant chromosome and of background chromosomes are determined from results of the sequencing. The determination of the relative amounts may count sequences of only certain length. A parameter derived from these amounts (e.g. a ratio) is compared to one or more cutoff values, thereby determining a classification of whether a fetal chromosomal aneuploidy exists. Prior to sequencing, the biological sample may be enriched for DNA fragments of a particular sizes.

The present disclosure provides methods for determining the ploidy status of a chromosome in a gestating fetus from genotypic data measured from a mixed sample of DNA comprising DNA from both the mother of the fetus and from the fetus, and optionally from genotypic data from the mother and father. The ploidy state is determined by using a joint distribution model to create a plurality of expected allele distributions for different possible fetal ploidy states given the parental genotypic data, and comparing the expected allelic distributions to the pattern of measured allelic distributions measured in the mixed sample, and choosing the ploidy state whose expected allelic distribution pattern most closely matches the observed allelic distribution pattern. The mixed sample of DNA may be preferentially enriched at a plurality of polymorphic loci in a way that minimizes the allelic bias, for example using massively multiplexed targeted PCR.

Aspects of the present invention include methods and compositions for determining the number of individual polynucleotide molecules originating from the same genomic region of the same original sample that have been sequenced in a particular sequence analysis configuration or process. In these aspects of the invention, a degenerate base region (DBR) is attached to the starting polynucleotide molecules that are subsequently sequenced (e.g., after certain process steps are performed, e.g., amplification and / or enrichment). The number of different DBR sequences present in a sequencing run can be used to determine / estimate the number of different starting polynucleotides that have been sequenced. DBRs can be used to enhance numerous different nucleic acid sequence analysis applications, including allowing higher confidence allele call determinations in genotyping applications.

A new method for genomic analysis, termed “Sequence-Based Karyotyping,” is described. Sequence-Based Karyotyping methods for the detection of genomic abnormalities, for diagnosis of hereditary disease, or for diagnosis of spontaneous genomic mutations are also described.

A method for screening individuals at risk for prostate cancer progression is disclosed. The method is useful for evaluating cells from patients at risk for recurrence of prostate cancer following surgery for prostate cancer. Specifically, the method uses specific Markovian nuclear texture factors, alone or in combination with other biomarkers, to determine whether the cancer will progress or lose organ confinement. In addition, methods of predicting the development of fatal metastatic disease by statistical analysis of selected biomarkers is also disclosed. The invention also contemplates a method that uses a neural network to analyze and interpret cell morphology data. Utilizing Markovian factors and other biomarkers as parameters, the network is first trained with a sets of cell data from known progressors and known non-progressors. The trained network is then used to predict prostate cancer progression in patient samples.

The present invention relates to genetic analysis and evaluation utilizing copy-number variants or polymorphisms. The methods utilize array comparative genomic hybridization and PCR assays to identify the significance of copy number variations in a subject or subject group.

A personalized physiological monitor utilizes an individual genome sequence along with genetic and medical research databases so as to define a person's genetic predisposition to disease, drug reactions and environmental sensitivities so as to enhance the ability of the monitor to determine the physiological status of the person.

The present invention describes changes in bacterial gastrointestinal, cutaneous and nasal microbiota associated various mammalian medical conditions. Described are diagnostic tests that arise from combining phylogenetic information about the families, genus, and species of the microbiome and their relative abundance with the metabolic information contained in the metatranscriptome to determine the presence and absence of a disease or medical condition. Provided are compositions of bacteria, co-cultures of bacteria and a carrier for use in treating the disclosed medical conditions. The described compositions restore or correct disease- or medical condition-related imbalances in the microbiome profile with culture-conditioned formulations in which the transcriptome activity of the administered organisms is optimized. Alternatively, formulations of metabolites that drive changes in the metatranscriptome native to the mammal that treat disease or a medical condition or restore health are taught.

Abstract of Disclosure A system and method used to assess animal behavior includes a module having sensors that collects a variety of physical and biological data from a test subject. Interpretation of the data is provided to assess the test subject's behavior, neurology, biochemistry and physiology. The module is useful in observing the effects of a drug on the test animal and providing information on the drug's signature. Another advantage is module's portability that allows it to be used in standard laboratory cages. This portability allows the animal to be tested in its own habitat, that can reduce any erroneous data due to stressing the animal when removed to a test cage. Additionally, the module's design allows for parallel data collection and interpretation from several laboratory animals undergoing different experiments. Multi-dimensional modeling of the test subject based the system's interpretation of the data allows pattern recognition of the drug signature, and predictive drug analysis.

A fractional concentration of clinically-relevant DNA in a mixture of DNA from a biological sample is determined based on amounts of DNA fragments at multiple sizes. For example, the fractional concentration of fetal DNA in maternal plasma or tumor DNA in a patient's plasma can be determined. The size of DNA fragments in a sample is shown to be correlated with a proportion of fetal DNA and a proportion of tumor DNA, respectively. Calibration data points (e.g., as a calibration function) indicate a correspondence between values of a size parameter and the fractional concentration of the clinically-relevant DNA. For a given sample, a first value of a size parameter can be determined from the sizes of DNA fragments in a sample. A comparison of the first value to the calibration data points can provide the estimate of the fractional concentration of the clinically-relevant DNA.

The invention provides methods for simultaneously amplifying multiple nucleic acid regions of interest in one reaction volume as well as methods for selecting a library of primers for use in such amplification methods. The invention also provides library of primers with desirable characteristics, such as minimal formation of amplified primer dimers or other non-target amplicons.

Methods for determining statistical models for predicting disease risks of a population are provided. Two types of data associated with members of the population are collected. The data may include both genetic and non-genetic types of data. A candidate statistical model is selected for calculating the disease risk. The model has a plurality of parameters and is a function of only one of the two types of data. A data weight is determined for each member of the population. Members having like data of the other type have like weights. The parameters of the model are optimized by fitting the collected data to the model taking into account of the weights.

The invention provides a method and a device for detecting mutated proteins. The method includes acquiring transcriptome data corresponding to samples; comparing the transcriptome data to mitochondrion databases and outputting non-mitochondrion sequences according to comparison results of the transcriptome data and the mitochondrion databases; transforming nucleotide sequences in the non-mitochondrion sequences into amino acid sequences, comparing the transformed amino acid sequences to protein databases and extracting amino acid sequences with homogenous rates in first set ranges and amino acid lengths in second set ranges from comparison results of the transformed amino acid sequences and the protein databases; comparing the extracted amino acid sequences with the homogenous rates in the first set ranges and the amino acid lengths in the second set ranges to NCBI (national center of biotechnology information) and determining the mutated proteins according to comparison results of the extracted amino acid sequences and the NCBI. According to the scheme, the method and the device have the advantage that the mutated proteins in the samples can be detected by the aid of the method and the device.

According to one embodiment, a malware detection and visualization system comprises one or more processors; and a storage module communicatively coupled to the one or more processors, the storage module comprises logic, upon execution by the one or more processors, that accesses a first set of information that comprises (i) information directed to a plurality of observed events and (ii) information directed to one or more relationships that identify an association between different observed events of the plurality of observed events; and generates a reference model based on the first set of information, the reference model comprises at least a first event of the plurality of observed events, a second event of the plurality of observed events, and a first relationship that identifies that the second event is based on the first event, wherein at least one of (i) the plurality of observed events or (ii) the one or more relationships constitutes an anomalous behavior is provided.